YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • ASCE
    • Journal of Environmental Engineering
    • View Item
    •   YE&T Library
    • ASCE
    • Journal of Environmental Engineering
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Simulation of Water Temperature in a Small Pond Using Parametric Statistical Models: Implications of Climate Warming

    Source: Journal of Environmental Engineering:;2016:;Volume ( 142 ):;issue: 003
    Author:
    Shakir Ali
    ,
    P. K. Mishra
    ,
    Adlul Islam
    ,
    N. M. Alam
    DOI: 10.1061/(ASCE)EE.1943-7870.0001050
    Publisher: American Society of Civil Engineers
    Abstract: Changes in temperature and precipitation patterns due to global warming are likely to affect the quantity and quality of water in different water bodies. Water temperature modeling techniques are usually employed to study the effects of global climate change on stream and river ecosystems. This study aims to identify a suitable air–water temperature relationship for a small aquatic pond in a semiarid region of India and examine the effects of increased water temperature on the small pond’s attributes. The performance of two parametric statistical models—simple linear regression (SLR) and four-parameter nonlinear logistic regression (NLR) models—was evaluated. The developed models were field tested for mean, minimum, and maximum air–water temperatures on daily, weekly, and monthly timescales. The model parameters were estimated from the measured air–water temperature time-series data using the least-squares optimization method. Model performance was evaluated using three statistical indicators—the index of agreement (d), Nash–Sutcliffe modeling efficiency (E), and root mean square error (RMSE). The performances of the SLR and NLR models were found to be comparable for all three data series and timescales. However, the NLR model was found to perform relatively better compared to the SLR model for all three timescales. Results also revealed better correlations between the measured and simulated water temperatures on weekly and monthly timescales compared to the daily timescale. Application of the SLR model for projecting changes in attributes of a small aquatic pond in a semiarid region of India under changing climate scenarios revealed a 1.3 to 3.7°C increase in pond water temperature with increases in air temperature from 1.5 to 4.3°C by the end of 2080. This increase in water temperature will cause the water evaporation rate to increase by 8.3–30.3% and the hydroperiod and saturated dissolved oxygen to decrease by 3–26 days and 2.2–6.5%, respectively.
    • Download: (6.145Mb)
    • Show Full MetaData Hide Full MetaData
    • Get RIS
    • Item Order
    • Go To Publisher
    • Price: 5000 Rial
    • Statistics

      Simulation of Water Temperature in a Small Pond Using Parametric Statistical Models: Implications of Climate Warming

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4243238
    Collections
    • Journal of Environmental Engineering

    Show full item record

    contributor authorShakir Ali
    contributor authorP. K. Mishra
    contributor authorAdlul Islam
    contributor authorN. M. Alam
    date accessioned2017-12-30T12:54:28Z
    date available2017-12-30T12:54:28Z
    date issued2016
    identifier other%28ASCE%29EE.1943-7870.0001050.pdf
    identifier urihttp://138.201.223.254:8080/yetl1/handle/yetl/4243238
    description abstractChanges in temperature and precipitation patterns due to global warming are likely to affect the quantity and quality of water in different water bodies. Water temperature modeling techniques are usually employed to study the effects of global climate change on stream and river ecosystems. This study aims to identify a suitable air–water temperature relationship for a small aquatic pond in a semiarid region of India and examine the effects of increased water temperature on the small pond’s attributes. The performance of two parametric statistical models—simple linear regression (SLR) and four-parameter nonlinear logistic regression (NLR) models—was evaluated. The developed models were field tested for mean, minimum, and maximum air–water temperatures on daily, weekly, and monthly timescales. The model parameters were estimated from the measured air–water temperature time-series data using the least-squares optimization method. Model performance was evaluated using three statistical indicators—the index of agreement (d), Nash–Sutcliffe modeling efficiency (E), and root mean square error (RMSE). The performances of the SLR and NLR models were found to be comparable for all three data series and timescales. However, the NLR model was found to perform relatively better compared to the SLR model for all three timescales. Results also revealed better correlations between the measured and simulated water temperatures on weekly and monthly timescales compared to the daily timescale. Application of the SLR model for projecting changes in attributes of a small aquatic pond in a semiarid region of India under changing climate scenarios revealed a 1.3 to 3.7°C increase in pond water temperature with increases in air temperature from 1.5 to 4.3°C by the end of 2080. This increase in water temperature will cause the water evaporation rate to increase by 8.3–30.3% and the hydroperiod and saturated dissolved oxygen to decrease by 3–26 days and 2.2–6.5%, respectively.
    publisherAmerican Society of Civil Engineers
    titleSimulation of Water Temperature in a Small Pond Using Parametric Statistical Models: Implications of Climate Warming
    typeJournal Paper
    journal volume142
    journal issue3
    journal titleJournal of Environmental Engineering
    identifier doi10.1061/(ASCE)EE.1943-7870.0001050
    page04015085
    treeJournal of Environmental Engineering:;2016:;Volume ( 142 ):;issue: 003
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian